4 citations · 6 across the 4 of their papers we have counts for
3 papers · 1 filter
MALIBU Benchmark: Multi-Agent LLM Implicit Bias Uncovered
Imran Mirza, Cole Huang, Ishwara Vasista +4
Multi-agent systems, which consist of multiple AI models interacting within a shared environment, are increasingly used for persona-based interactions. However, if not carefully de…
TRUTH DECAY: Quantifying Multi-Turn Sycophancy in Language Models
Joshua Liu, Aarav Jain, Soham Takuri +5
Rapid improvements in large language models have unveiled a critical challenge in human-AI interaction: sycophancy. In this context, sycophancy refers to the tendency of models to…
ChunkRAG: Novel LLM-Chunk Filtering Method for RAG Systems
Ishneet Sukhvinder Singh, Ritvik Aggarwal, Ibrahim Allahverdiyev +4
Retrieval-Augmented Generation (RAG) systems using large language models (LLMs) often generate inaccurate responses due to the retrieval of irrelevant or loosely related informatio…